We are seeking an experienced Mid/Mid+ Data Scientist with expertise in Large Language Models (LLMs) such as GPT, Claude, and related technologies to join our team in Ukraine. The ideal candidate will have a strong background in natural language processing (NLP), machine learning, and deep learning models. They will play a critical role in developing and deploying cutting-edge LLM applications to drive innovation across our product lines.
Responsibilities:
- Design, develop and optimize Large Language Models for various NLP tasks such as text generation, summarization, translation, and question-answering
- Conduct research and experiments to push the boundaries of LLM capabilities and performance
- Collaborate with cross-functional teams (engineering, product, research) to integrate LLMs into product offerings
- Develop tools, pipelines and infrastructure to streamline LLM training, deployment and monitoring
- Analyze and interpret model outputs, investigate errors/anomalies, and implement strategies to improve accuracy
- Stay current with the latest advancements in LLMs, NLP and machine learning research
- Communicate complex technical concepts to both technical and non-technical stakeholders
Requirements:
- MS or PhD degree in Computer Science, Data Science, AI, or a related quantitative field
- 4+ years of hands-on experience developing and working with deep learning models, especially in NLP/LLMs
- Expert knowledge of Python, PyTorch, TensorFlow, and common deep learning libraries
- Strong understanding of language models, attention mechanisms, transformers, sequence-to-sequence modeling
- Experience training and fine-tuning large language models
- Proficiency in model deployment, optimization, scaling and serving
- Excellent problem-solving, analytical and quantitative abilities
- Strong communication skills to present technical information clearly
- Ability to work collaboratively in a team environment
- Fluency in Ukrainian and English
Preferred:
- Research experience in LLMs, NLP, machine learning
- Experience working with multi-modal data (text, image, audio)
- Knowledge of cloud platforms like AWS, GCP for model training
- Understanding of MLOps and production ML workflows
- Background in information retrieval, knowledge graphs, reasoning